{"id":3970877,"url":"https://alion.io/job/tem-energy-senior-staff-machine-learning-engineer-ml-platform","title":"Senior Staff Machine Learning Engineer - ML Platform","company":{"id":580,"name":"TEM Energy","domain":"tem.energy","url":"https://alion.io/company/tem","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":88,"open_postings":4,"ghost_share":0,"stale_share":0.5,"repost_share":0,"time_to_fill_p50_days":56,"computed_at":"2026-11-09T06:03:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["GB"],"hiring_countries_total":1,"salary":{"min":115000,"max":127000,"currency":"GBP","period":"year","gross":null,"usd_annual":169632},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Time Series","optional":false}],"status":"live","first_seen_at":"2026-11-09T15:21:02Z","employer_posted_date":"2026-11-09","last_verified_at":"2026-11-10T02:54:07Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Who We Are:\nWe are rebuilding the energy transaction, making it transparent and fair.\nWe're rebuilding how energy is bought and sold. That means cutting out middlemen, connecting businesses directly with renewable generators, and ensuring every transaction is traceable and transparent.\nWe're a 160+ person team - operators, data scientists, engineers, customer champions and energy experts - backed by top-tier investors including Lightspeed Venture Partners, Hitachi Ventures, Allianz, AlbionVC and Atomico. We closed a $75M Series B round in early 2026, taking our total funding to $94M, and we now power energy for over 4,000 UK businesses across 8,500+ sites, with over £75m in value returned to businesses and generators so far.\nWe're a technology company solving the energy industry, not an energy company. Some people call us a neo-utility, the neo-bank idea, applied to energy.\nThe industry is noticing. We were crowned Europe's Most Exciting Tech Company at the GP Bullhound Allstars awards, came in at #6 on LinkedIn's Top Startups 2026 in the UK, #7 on the Scaling Europe 50 of Europe's fastest-growing companies, and #14 on Sifted's AI 100.\nLearn more about us on our website.\nThe Role\nWe're hiring a Senior Staff Machine Learning Engineer (ML Platform).\nIn this role you will work on the ML platform inside Rosso, improving the infrastructure, tooling and standards that let us develop, train, evaluate, monitor and iterate models quickly and with confidence. You know ML engineering deeply and will contribute to model improvements where it matters, with a primary focus on building the platform and tools that help the whole team work faster and better.\nYou will:\nBuild the systems that let us deploy, iterate, and scale ML and optimisation models without friction.\n\nGive us clear operational visibility into how every model is performing, and where it is not.\n\nBuild evaluation and backtesting tooling for ML models, pricing and trading strategies.\n\nTake ownership of model inference and training in production. The role includes work-hours on-call responsibility, and may extend to out-of-hours in the future.\n\nThe metric this role moves: number of effective forecasting & optimisation ML models deployed within our stack. Success means a new model goes from idea to trusted production with standard tooling, clear evaluation and confidence from day one.\nResponsibilities\nML infrastructure and deployment\nShape and improve the infrastructure that underpins ML deployment across pricing, forecasting, prediction and optimisation.\n\nDesign and build the systems that let us take a model from experiment to production quickly and repeatably.\n\nScale models and pipelines as volume, markets and complexity grow.\n\nObservability and quality\nBuild the tooling and code that ensure models run reliably and produce sensible results.\n\nCreate operational and analytical monitoring so we catch failures, drift and degradation early.\n\nBuild confidence in our input data through validation, checks and clear data contracts.\n\nEvaluation, experimentation and backtesting tooling\nDevelop the tooling and abstractions to evaluate ML models and optimisation algorithms during experimentation, including backtesting of pricing and trading strategies.\n\nStandardise processes and data structures so each new model is faster to ship than the last.\n\nData systems\nMature the data systems (databases, pipelines, validations, ingestions) that let us manage model rollouts safely.\n\nOwnership\nOwn model inference and training in production, including on-call during working hours. There is no out-of-hours on-call today, though this may change as the platform grows.\n\nContribute directly to model improvements where your ML expertise moves the needle.\n\nRequirements\nMust haves\nStrong ML engineering foundations: experience developing, deploying and improving ML models in production.\n\nExperience contributing to or building an MLOps stack, including ensuring reliability and observability.\n\nExperience with the scaling pressures and complexities of large-data ML workloads, and designing data systems (pipelines, databases, query patterns) to handle them.\n\nExperience with time-series forecasting in particular.\n\nKnowing what good looks like in a ML platform, and being ready to build it in a high-ownership environment.\n\nBonus points\nProbabilistic modelling and quantifying uncertainty, for example probabilistic forecasts, calibration or Bayesian methods.\n\nQuant tooling experience, such as building backtesting frameworks or evaluation tooling for trading or optimisation strategies.\n\nAny of the above in finance or energy, including automated trading systems.\n\nBenefits & Perks\nSalary aligned to internal benchmarks and reviewed twice a year.\n\nStock options so everyone has ownership in our mission.\n\n25 days holiday plus public holidays. Swap public holidays for the ones that matter most to you, and enjoy your birthday off.\n\nRemote first and flexible working, with clear core hours and no internal meetings on Friday afternoons.\n\nHome working and wellbeing budgets:\nUp to GBP1,200 or EUR1,200 per year for your remote setup.\n\nUp to GBP150 or EUR150 per month for wellbeing.\n\nInterview Process\nWe move fast. Most processes take 2 to 3 weeks from first chat to offer. If you need us to adapt anything, let us know.\nIntro call with Talent, 30 minutes.\n\nBehavioural interview, 30 minutes.\n\nSkills interview 90 minutes\n\nBar Raiser interview with leadership stakeholders, 30 minutes.\n\nWe welcome applications from people of all backgrounds, experiences, and identities, including those that are traditionally underrepresented in the tech and energy sectors. If you’re excited about this role but not sure you meet every requirement, we’d still love to hear from you. Your unique perspective could be exactly what we’re looking for.","description_format":"text","description_chars":5819,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Flexible schedule","Stock options"],"hiring_locations":[{"name":"United Kingdom","iso":"GB","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Smart Grid","Energy Management"],"lifecycle":[{"event":"open","at":"2026-11-09T16:02:33Z"}],"visa":[{"country":"GB","licensed_sponsor":true,"adverts_offering_sponsorship_24m":0,"sanctioned_now":false,"evidence":"Licensed UK visa sponsor (Skilled Worker)","filings_12m":null,"filings_prev_12m":null,"green_card_filings_12m":null,"median_offered_wage_usd":null,"route":"Skilled Worker","cap_exempt":false,"checked_at":"2026-11-09T07:32:21+00:00","sources":["UK Home Office: register of licensed sponsors (workers)"],"filings_for_role_12m":0}],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":56,"reasons":["conf:2","win:early"],"computed_at":"2026-11-10T04:59:11Z"},"pay":{"stated_usd_annual":169632,"is_top_pay":false},"html_url":"https://alion.io/job/tem-energy-senior-staff-machine-learning-engineer-ml-platform","json_url":"https://alion.io/job/tem-energy-senior-staff-machine-learning-engineer-ml-platform.json","meta":{"generated_at":"2026-11-10T04:59:11Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":11660,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-11T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.1,"usd":0.01,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":580},"rest":"https://alion.io/mcp/rest/get_company?id=580"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Ftem-energy-senior-staff-machine-learning-engineer-ml-platform"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":2,"usd":0.2},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Ftem-energy-senior-staff-machine-learning-engineer-ml-platform"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.1,"usd":0.01},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Ftem-energy-senior-staff-machine-learning-engineer-ml-platform"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/tem-energy-senior-staff-machine-learning-engineer-ml-platform\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Ftem-energy-senior-staff-machine-learning-engineer-ml-platform"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3970877}},{"tool":"search_jobs","arguments":{"company":"tem.energy","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3970877},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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